PROGRAMMING LANGUAGES YOU WON’T USE BY 2030
7 min
May 04 2021
Programming languages are disappearing. It's an inescapable fact of life: the old and tired are inevitably replaced by the new and better (or at least a little different). While it's impossible to predict which languages will actually persist over the next decade (with the exception of Python and JavaScript; I think both of them will remain), it's worth asking which languages are on the road to oblivion—after all, you don't want to waste time learning something that won't be useful for a long time.

Why Will Objective-C Disappear?

Apple’s original programming language has been alive for 36 years, and it seems certain that some legacy apps will still incorporate it 10 years from now. But the chances of you actually working with it by the end of the decade? Pretty much zero, unless you land a job maintaining some obscure iOS app that a company absolutely refuses to update under any circumstances.
Apple is dedicated to ensuring that Swift, which launched in 2014, totally replaces Objective-C. Despite that push, however, Objective-C has managed to maintain much of its popularity and market-share. Why is that? The explanation is pretty straightforward: Swift didn’t emerge fully featured, and its creators have spent the past five years adding crucial features such as ABI stability. That’s encouraged many iOS and macOS developers to stick with Objective-C for the time being.
As Swift becomes more robust, though, the use-case for Objective-C will fade. Over the next ten years, companies will also re-write big chunks of their iOS/macOS codebase in Swift, lessening the need to maintain Objective-C legacy code. If you’re interested in building for Apple’s ecosystem, now’s the time to learn the various features of Swift, including Strings, Arrays, and Package Manager.

Perl Will Fade Away

Yes, Perl has its own adherents. Every time an article appears that declares Perl on the list of endangered languages, fans point to the number of open Perl jobs currently available, as well as the fact that there is still an active developer community around Perl and its potential evolution into something new and interesting.
However, RedMonk and the TIOBE index show that Perl is in decline, and while you may disagree with how any site ranks programming languages, if their different methodologies come to the same conclusion, then it's safe to say that something is really going on here. Adherents like to point out Perl's high performance and ability to scale (hence its lovely nickname “Swiss Army Chainsaw”), but other languages—most notably Python—have begun to overshadow it in terms of implementation, libraries, and features.
The number of people using Perl is expected to decline further over the next ten years, putting the language at serious risk of disappearing altogether.

CoffeeScript is Burned

According to codementor.io, CoffeeScript (a programming language that compiles to JavaScript; yes, we’re counting it) ranked among the worst languages for community engagement and growth in 2019. “CoffeeScript’s Facebook community was nonexistent this year and it ranked near the bottom of the pack for Freenode IRC, Twitter, GitHub, and Stack Overflow tags,” the website wrote in a note accompanying its data. “/r/coffeescript, unfortunately, also had the dubious honor of being the least popular subreddit on our list of languages.”
CoffeeScript has also experienced a decline in Google Trends. Barring some remarkable event that returns it to relevance, it seems unlikely that CoffeeScript will be broadly used within ten years.

Why Is R Dead?

Data science is only becoming more crucial to many companies, leading to a spike in job postings for data scientists, data analysts, and data engineers. Core programming languages to data science include Python, R, and SQL—but there are a lot of signs that Python has begun to swallow up R, which was developed for statisticians and data analysts.
“Behind Python’s growth is a speedily-expanding community of data science professionals and hobbyists—and the tools and frameworks they use every day,” read the latest edition of GitHub’s State of the Octoverse. “These include the many core data science packages powered by Python that are both lowering the barriers to data science work and proving foundational to projects in academia and companies alike.”
For years, various sites have tracked Python gaining ground at R’s expense. In 2018, a KDnuggets poll traced that decline in R usage in favor of Python (especially among tech pros who utilized both languages). Meanwhile, a separate survey from Burtch Works revealed that Python use among analytics professionals grew from 53 percent to 69 percent over that same time two-year period, while the R user-base shrank by nearly a third.
There’s no reason to think this trend won’t continue over the next few years, putting R at serious risk of being completely supplanted by Python.
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